Bidirectional path tracing doesn't do anything clever to "try to connect" paths from light sources and cameras. The approach is just
- Trace random paths from light sources until they terminate (usually decided with Russian roulette).
- Trace random paths from the camera (usually N per pixel, or you can use more paths in noisy areas) until they terminate.
- Try to connect each point in a camera path with each point in a light path, using a simple line test. If it succeeds, that color is added to the pixel from which the camera path originated.
At least that's my understanding; I've only implemented simpler algorithms and read a bit about bidirectional path tracing.
> If we are calculating on a per pixel basis, that means bundling multiple paths together to figure out what the weighted return will look like. How can this all be computed with any kind of efficiency without cheating?
Right, we still need to consider many paths per pixel to get a high quality image. But it converges faster than most other Monte Carlo techniques.
- Trace random paths from light sources until they terminate (usually decided with Russian roulette).
- Trace random paths from the camera (usually N per pixel, or you can use more paths in noisy areas) until they terminate.
- Try to connect each point in a camera path with each point in a light path, using a simple line test. If it succeeds, that color is added to the pixel from which the camera path originated.
At least that's my understanding; I've only implemented simpler algorithms and read a bit about bidirectional path tracing.
> If we are calculating on a per pixel basis, that means bundling multiple paths together to figure out what the weighted return will look like. How can this all be computed with any kind of efficiency without cheating?
Right, we still need to consider many paths per pixel to get a high quality image. But it converges faster than most other Monte Carlo techniques.